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The purpose of this paper is to achieve the trajectory tracking measurement of a moving target based on double position sensitive detectors (PSDs).

In this paper, first, a double PSD-based measurement system including hardware system and software system is built up. Then, the working principle is studied to calculate parameters, and calibration experience is conducted. Finally, this double PSD-based measurement system is used to test angular displacement and axial displacement on the tool magazine and automatic tool changer.

In the experiment, the maximum position error of a space point based on double PSD measurement system is 0.8566 mm, and the average error is 0.4716 mm. These results show that the built double PSD-based measurement system of trajectory tracking of a moving target is reasonable.

Combining the characteristics of the PSD and principles of binocular visual measurement, a non-contact three-dimensional measuring system based on double PSDs is developed. The designed double-based measurement system is quite suitable for measurement of a fast-changing illuminant or in the case that the tracking accuracy is not tight.

In the assembly process of the satellite, there will be multiple installation and disassembly operations for the solar wing and the main satellite body (or simulator). However, the traditional method of orientation adjustment by theodolite and two-axis turntable is difficult to coordinate three rotation angles of yaw, pitch and roll, which leads to the complexity of actual operation and dependency on manual experience. Therefore, this paper aims to propose a new method to achieve rapid and precise orientation adjustment.

The similarity relation of the orientation variation matrix in a different coordinate system is studied, and a mapping model of the similarity relation is established. By using multiple element matrices to construct the original rotation matrix, the mapping is solved in quaternion form. Taking the theodolite as a measuring instrument and the Stewart platform as a control equipment, an experiment on installing the solar wing is performed to validate the effectiveness of the algorithm.

Based on the solving algorithm, the orientation adjustment process is simplified to a three-step fixed mode, which is three adjustments to get the parameter of the mapping model, one to adjust the component in place and another to further fine tuning. The final orientation deviation is less than 0.003° and close to the level of using a laser tracker, achieving the required accuracy of 0.0115°.

This paper reveals the similarity relation of the variation matrix in the process of orientation adjustment and presents a new method to achieve rapid and precise orientation adjustment for the large-scale component.

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

This paper aims to propose a hand–eye calibration method of arc welding robot and laser vision sensor by using semidefinite programming (SDP).

The conversion relationship between the pixel coordinate system and laser plane coordinate system is established on the basis of the mathematical model of three-dimensional measurement of laser vision sensor. In addition, the conversion relationship between the arc welding robot coordinate system and the laser vision sensor measurement coordinate system is also established on the basis of the hand–eye calibration model. The ordinary least square (OLS) is used to calculate the rotation matrix, and the SDP is used to identify the direction vectors of the rotation matrix to ensure their orthogonality.

The feasibility identification can reduce the calibration error, and ensure the orthogonality of the calibration results. More accurate calibration results can be obtained by combining OLS + SDP.

A set of advanced calibration methods is systematically established, which includes parameters calibration of laser vision sensor and hand–eye calibration of robots and sensors. For the hand–eye calibration, the physics feasibility problem of rotating matrix is creatively put forward, and is solved through SDP algorithm. High-precision calibration results provide a good foundation for future research on seam tracking.

Automation planners need to view retrospective conversion from an informed and balanced perspective. They must consider: 1) the technical dimensions of retrospective conversion, 2) the appropriate standards to employ, 3) the proper relationship of conversion activities to the entire automation project, and 4) options available for converting a bibliographic database into machine‐readable format. Six prominent consultants provide important advice on this topic.

Visually impaired people have long been living in the dark. They cannot realize the colorful world with their vision, so they rely on hearing, touch and smell to feel the space they live in. Lacking image information, they face challenges in the external environment and barrier spaces. They face danger that is hundreds of times higher than that faced by normal people. Especially during outdoor activities, they can only explore the surrounding environment aided by their hearing and crutches and then based on a vague impression speculate where they are located. To let the blind confidently take each step, this paper proposes sticking the electronic tag of the radio-frequency identification (RFID) system on the back of guide bricks.

Thus, the RFID reader, ultrasonic sensor and voice chip on a wheeled mobile robot link the front end to the crutch. Once the blind person nears a guide brick, the RFID will read the message on the tag through the voice broadcast system, and a voice will inform the visually impaired person of the direction to walk and information of the surrounding environment. In addition, the CMOS image sensor set up in the wheeled mobile robot is used to detect the black marking on the guide brick and to guide the blind to walk forward or turn around between the two markings. Finally, the lithium battery charging control unit was installed on the wheeled mobile robot. The ATtiny25 microcontroller conducts the battery charge and discharge control and monitoring of the current battery capacity.

The development of this system will let visually impaired people acquire environmental information, road guidance function and nearby traffic information.

Through rich spatial environment messages, the blind can have the confidence and courage to go outside.

The purpose of this paper is the presentation and research of a novel sensor fusion-based system for obstacle detection and identification, which uses the millimeter-wave radar to detect the position and velocity of the obstacle. Afterwards, the image processing module uses the bounding box regression algorithm in deep learning to precisely locate and identify the obstacles.

Unlike the traditional algorithms that use radar and vision to detect obstacles separately, the purposed method of this paper uses radar to determine the approximate location of obstacles and then uses bounding box regression to achieve accurate positioning and recognition. First, the information of the obstacles can be acquired by the millimeter-wave radar, and the effective target is extracted by filtering the data. Then, use coordinate system conversion and camera parameter calibration to project the effective target to the image plane, and generate the region of interest (ROI). Finally, based on image processing and machine learning techniques, the vehicle targets in the ROI are detected and tracked.

The millimeter wave is used to determine the presence of an obstacle, and the deep learning algorithm of the image is combined to determine the shape and the class of the obstacle. The experimental results indicate that the detection rate of this method is up to 91.6 per cent, which can better implement the perception of the environment in front of the vehicle.

The originality is based on the combination of millimeter-wave sensors and deep learning. Using the bounding box regression algorithm in RCNN, the ROI detected by radar is analyzed to realize real-time obstacle detection and recognition. This method does not require processing the entire image, greatly reducing the amount of data processing and improving the efficiency of the algorithm.

In the digital assembly system of large aircraft components (LAC), the docking trajectory of LAC is an important factor affecting the docking accuracy and stability of the LAC. The main content of docking trajectory planning is how to move the LAC from the initial posture and position to the target posture and position (TPP). This paper aims to propose a trajectory planning method of LAC based on measured data.

First, the posture and position error model of the wing is constructed according to the measured data of the measurement points (MPs) and the fork lug joints. Second, the particle swarm optimization algorithm based on the dynamic inertia factor is used to optimize the TPP of the wing. Third, to ensure the efficiency and stability of posture adjustment, the S-shaped curve is used as the motion trajectory of LAC, and the parameters of the trajectory are solved by the generalized multiplier method. Finally, a series of docking experiments are carried out.

During the process of posture adjustment, the motion of the numerical control locator (NCL) is stable, and the interaction force between the NCLs is always within a reasonable range. After the docking, the MPs are all within the tolerance range, and the coaxiality error of the fork lug hole is less than 0.2 mm.

In this paper, the measured data rather than the theoretical design model is used to solve the TPP, which improves the docking accuracy of LAC. Experiment results show that the proposed trajectory method can complete the LAC docking effectively and improve the docking accuracy.

Determinative locating and riveting distortions are highly coupled at assembly locale. Recent methods only take every tested or assumed locating errors at the mating surface into the process planning for the assemblies in a simple form. However, the growth of part number makes it nearly infeasible to take every locating error at every mating surface into the dimensional precision calculation. This paper aims to provide a solid riveting process planning for the reduction of practical locating-related distortions.

Large-scale metrology firstly measures the determinative coordinates for the locating-deviated key points. Iterative finite element (FE) analyses then calculate the riveting-related key point distortions from every rivet upsetting directions (UDs) and assembly sequence. These key points on the actual assembly contour and relative FE nodes yield two virtual planes. Virtual plane manipulation adds the riveting distortions into the locating-deviated coordinates. Finally, optimal algorithm integrates the iterative FE analyses with virtual plane manipulation.

Case studies validate that the virtual plane manipulation coincides with the test well, and the proposed method has good compensation of practical locating distortion.

The optimized rivet UDs may be set in a chaotic distribution, which may complicate the abundant riveting operations and the assembly appearance. Therefore, the use of automatic riveting systems can overcome the operational complexity, and the industrial design of rivet UD distribution will improve the assembly appearance.

The optimized UDs and assembly sequence are for assembly workers or automatic riveting systems.

The proposed method is the first to reduce the determinative locating distortion by a novel and efficient solid riveting process planning in detail, and the solid riveting process designed is conservative and accurate for practice.